J. Upchurch
Real-Time Innovations,
United States
Keywords: self‑organizing multi‑agent systems, data distribution service (DDS), foundation‑model orchestration, simulation‑to‑ops, autonomous robotics, industrial IoT
Summary:
GENESIS is a self‑organizing, distributed AI framework that composes agents and foundation models into task chains discovered at execution time. Built on RTI Connext DDS (TRL 9, deployed in >1600 DoD applications), it provides real‑time, secure, and observable data exchange across simulations, edge devices, and enterprise systems. Rather than hard‑coding pipelines or centralizing all logic in the cloud, GENESIS allows services to advertise capabilities and constraints, then forms, monitors, and adapts chains on the fly under policy control—preserving auditability and human oversight. Transformational: GENESIS converts AI from monolithic applications into composable capabilities that can be re‑used across missions and domains. Runtime discovery eliminates brittle integrations and reduces time‑to‑demo and time‑to‑deployment. Policy‑governed coordination and built‑in observability support safety cases and certification workflows. Different: Traditional orchestrators assume fixed workflows or cloud hubs. GENESIS is decentralized, transport‑level interoperable, and latency‑aware, operating where data lives (lab, factory floor, vehicle, field). DDS provides deterministic, standards‑based messaging and discovery across vendors and networks, while GENESIS integrates heterogeneous models and tools without re‑architecting. Impact: Organizations gain resilient automation that scales from prototype to fleet. Defense, autonomous robotics, and simulation/training can fuse live and synthetic data, accelerate V&V, and govern AI actions under strict constraints. Industrial users reduce backhaul and egress costs, improve uptime at the edge, and keep sensitive data local while maintaining interoperability. Maturity and availability: GENESIS is conservatively TRL 5: integrated components validated in relevant simulated environments and exercised with DDS‑based subsystems; portions may qualify as TRL 6 where prototypes have been demonstrated in realistic operational contexts. An experimental, unsupported RTI Labs release is planned in Nov 2025 and will enable public iteration, third‑party integrations, and standards alignment. Value to customers and partners: Faster delivery with lower integration risk; leaner infrastructure via edge execution; improved safety/compliance through governed actions and auditable flows; and a vendor‑neutral surface for packaging perception, planning, simulation, and analytics as discoverable services. As more capabilities join the network, value compounds while avoiding lock‑in.